Query processing, indexing, transactions, data quality, and modern database architectures.
31 curated papers31 papers
Enforces priority differentiation through replica assignment while retaining high utilization through controlled capacity borrowing.
Combines symbolic database analysis, language-model inference, and targeted user questions to construct usable analytic semantic schemas.
Modern database management systems (DBMSs) expose hundreds of configuration knobs that critically influence performance. Existing automated tuning methods either adopt a data-driven paradigm, which incurs substantial overhead, or rely on manual-driven heuristics extracted from database documentation, which are often limited and overly generic.
Reviews recent work that makes the optimal algorithm for acyclic joins practical in modern query engines.
Balances lookup, range-query, update, stability, and space objectives in one learned-index framework.
With the proliferation of Large Language Models (LLMs) in Business Intelligence (BI), existing solutions face critical challenges in industrial deployments: functionality deficiencies from legacy systems failing to meet evolving LLM-era user demands, interaction limitations from single-round SQL generation paradigms inadequate for multi-round…
There has been considerable interest in leveraging GPUs' computational power and high memory bandwidth for analytical database workloads. However, their limited memory capacity remains a fundamental limitation for databases whose sizes far exceed the GPU memory size.
Acyclic conjunctive queries form the backbone of most analytical workloads, and have been extensively studied in the literature from both theoretical and practical angles. However, there is still a large divide between theory and practice.
Graphs are ubiquitous data structures used in a large spectrum of applications, spanning from transportation networks, financial networks, social networks, product-order transactions and biomedical applications [33]. A recent survey on the usage of graph applications from real users has highlighted the fact that analytics is the most time-consuming task…
The recent ISO SQL:2023 standard adopts SQL/PGQ (Property Graph Queries), facilitating graph-like querying within relational databases. This advancement, however, underscores a significant gap in how to effectively optimize SQL/PGQ queries within relational database systems.
Join evaluation is one of the most fundamental operations performed by database systems and arguably the most well-studied problem in the Database community. A staggering number of join algorithms have been developed, and commercial database engines use finely tuned join heuristics that take into account many factors including the selectivity of…
Cardinality estimation (CardEst) is essential for optimizing query execution plans. Recent ML-based CardEst methods achieve high accuracy but face deployment challenges due to high preparation costs and lack of transferability across databases.
Many organizations have embraced the "Lakehouse" data management paradigm, which involves constructing structured data warehouses on top of open, unstructured data lakes. This approach stands in stark contrast to traditional, closed, relational databases and introduces challenges for performance and stability of distributed query processors.
CXL-based disaggregated memory systems offer options to expand the memory beyond the limits of a single server via cache-coherent memory expansion cards or memory pools. Especially, In-Memory Database Management Systems (IMDBMSs) can benefit from alleviating two critical constraints: (1) limited memory capacity in a server and (2) long restart time…
SQL has been extremely successful as the de facto standard language for working with data. Virtually all mainstream database-like systems use SQL as their primary query language.
Distributed databases have become indispensable in contemporary computing and data processing, owing to their pivotal role in ensuring high availability and scalability. They effectively cater to the requirements of data management and high-concurrency access.
In recent years at Tencent, we have observed that the use of multiple NoSQL databases for storing business data with diverse models has led to increased programming and deployment costs, as well as inefficient maintenance and underutilized resources. In this paper, we report X-Stor, a cloud-native NoSQL database system that supports multiple data models…
Maximizing transaction throughput is key to high-performance database systems, which focus on minimizing data access conflicts to improve performance. However, finding efficient schedules that reduce conflicts remains an open problem.
Database research and development is heavily influenced by benchmarks, such as the industry-standard TPC-H and TPC-DS for analytical systems. However, these twenty-year-old benchmarks neither capture how databases are deployed nor what workloads modern cloud data warehouse systems face these days.
Abstract To provide applications with the ability to analyze fresh data and eliminate the time-consuming ETL workflow, hybrid transactional and analytical (HTAP) systems have been developed to serve online transaction processing and online analytical processing workloads in a single system. In recent years, HTAP systems have attracted considerable…
Memory disaggregation can potentially allow memory-optimized range indexes such as B+-trees to scale beyond one machine while attaining high hardware utilization and low cost. Designing scalable indexes on disaggregated memory, however, is challenging due to rudimentary caching, unprincipled offloading and excessive inconsistency among servers.
The evaluation of top-k conjunctive queries, a staple in business analysis, often requires evaluating the conjunctive query prior to filtering the top-k results, leading to a significant computational overhead within Database Management Systems (DBMSs). While efficient algorithms have been proposed, their integration into DBMSs remains arduous.
Index tuning aims to find the optimal index configuration for an input workload. It is often a time-consuming and resource-intensive process, largely attributed to the huge amount of "what-if" calls made to the query optimizer during configuration enumeration.
Query performance (e. g.
Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases. However, such a standard cannot be taken for granted when dealing with tables "in the wild".
Classifies hybrid transactional/analytical systems by storage architecture and reviews synchronization, optimization, and scheduling techniques.
Uses cardinality-estimation consistency rules to find confirmed performance bugs in widely used database systems.
Distributed protocols such as 2PC and Paxos lie at the core of many systems in the cloud, but standard implementations do not scale. New scalable distributed protocols are developed through careful analysis and rewrites, but this process is ad hoc and error-prone.
Database systems often rely on historical query traces to perform workload-based performance tuning. However, real production workloads are time-evolving, making historical queries ineffective for optimizing future workloads.
Join ordering and query optimization are crucial for query performance but remain challenging due to unknown or changing characteristics of query intermediates, especially for complex queries with many joins. Over the past two decades, a spectrum of techniques for adaptive query processing (AQP)---including inter-/intra-operator adaptivity and tuple…
Efficient query optimization is crucial for database management systems. Recently, machine learning models have been applied in query optimizers to generate better plans, but the unpredictable performance regressions prevent them from being truly applicable.